As regional grids increase penetrations of variable renewable electricity (VRE) sources, demand-side management (DSM) presents an opportunity to reduce electricity-related emissions by shifting consumption patterns in a way that leverages the large diurnal fluctuations in the emissions intensity of the electricity fleet. Here we explore residential precooling, a type of DSM designed to shift the timing of air-conditioning (AC) loads from high-demand periods to periods earlier in the day, as a strategy to reduce peak period demand, CO2emissions, and residential electricity costs in the grid operated by the California Independent System Operator (CAISO). CAISO provides an interesting case study because it generally has high solar generation during the day that is replaced by fast-ramping natural gas generators when it drops off suddenly in the early evening. Hence, CAISO moves from a fleet of generators that are primarily clean and cheap to a generation fleet that is disproportionately emissions-intensive and expensive over a short period of time, creating an attractive opportunity for precooling. We use EnergyPlus to simulate 480 distinct precooling schedules for four single-family homes across California’s 16 building climate zones. We find that precooling a house during summer months in the climate zone characterizing Downtown Los Angeles can reduce peak period electricity consumption by 1–4 kWh d−1and cooling-related CO2emissions by as much as 0.3 kg CO2 d−1depending on single-family home design. We report results across climate zone and single-family home design and show that precooling can be used to achieve simultaneous reductions in emissions, residential electricity costs, and peak period electricity consumption for a variety of single-family homes and locations across California.
This content will become publicly available on December 8, 2024
The California Independent System Operator (CAISO) utilizes a system-wide, voluntary demand response (DR) tool, called the Flex Alert program, designed to reduce energy usage during peak hours, particularly on hot summer afternoons when surges in electricity demand threaten to exceed available generation resources. However, the few analyses on the efficacy of CAISO Flex Alerts have produced inconsistent results and do not investigate how participation varies across sectors, regions, population demographics, or time. Evaluating the efficacy of DR tools is difficult as there is no ground truth in terms of what demand would have been in the absence of the DR event. Thus, we first define two metrics that to evaluate how responsive customers were to Flex Alerts, including the
- Award ID(s):
- 1845931
- NSF-PAR ID:
- 10480400
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research: Energy
- Volume:
- 1
- Issue:
- 1
- ISSN:
- 2753-3751
- Page Range / eLocation ID:
- 015002
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
As renewable electricity generation continues to increase in the United States (US), considerable effort goes into matching heterogeneous supply to demand at a subhour time-step. As a result, some electric providers offer incentive-based programs for residential consumers that aim to reduce electric demand during high-demand periods. There is little research into determinants of consumer response to incentive-based programs beyond typical sociodemographic characteristics. To add to this body of literature, this paper presents the findings of a dichotomous choice contingent valuation (CV) survey targeting US ratepayers’ participation in a direct-load-control scheme utilizing a smart thermostat designed to reallocate consumer electricity demand on summer days when grid stress is high. Our results show approximately 50% of respondents are willing to participate at a median willingness-to-accept (WTA) figure of USD 9.50 (95% CI: 3.74, 15.25) per month that lasts for one summer (June through August)—or slightly less than USD 30 per annum. Participation is significantly affected by a respondent’s attitudes and preferences surrounding various environmental and institutional perspectives, but not by sociodemographic characteristics. These findings suggest utilities designing direct-load-control programs may improve participation by designing incentives specific to customers’ attitudes and preferences.more » « less
-
Enabling participation of demand-side flexibility in electricity markets is key to improving power system resilience and increasing the penetration of renewable generation. In this work we are motivated by the curtailment of near-zero-marginal-cost renewable resources during periods of oversupply, a particularly important cause of inefficient generation dispatch. Focusing on shiftable load in a multi-interval economic dispatch setting, we show that incompatible incentives arise for loads in the standard market formulation. While the system's overall efficiency increases from dispatching flexible demand, the overall welfare of loads can decrease as a result of higher spot prices. We propose a market design to address this incentive issue. Specifically, by imposing a small number of additional constraints on the economic dispatch problem, we obtain a mechanism that guarantees individual rationality for all market participants while simultaneously obtaining a more efficient dispatch. Our formulation leads to a natural definition of a uniform, time-varying flexibility price that is paid to loads to incentivize flexible bidding. We provide theoretical guarantees and empirically validate our model with simulations on real-world generation data from California Independent System Operator (CAISO).more » « less
-
more » « less
Abstract Current projections of the climate-sensitive portion of residential electricity demand are based on estimating the temperature response of the mean of the demand distribution. In this work, we show that there is significant asymmetry in the summer-time temperature response of electricity demand in the state of California, with high-intensity demand demonstrating a greater sensitivity to temperature increases. The greater climate sensitivity of high-intensity demand is found not only in the observed data, but also in the projections in the near future (2021–2040) and far future periods (2081–2099), and across all (three) utility service regions in California. We illustrate that disregarding the asymmetrical climate sensitivity of demand can lead to underestimating high-intensity demand in a given period by 37–43%. Moreover, the discrepancy in the projected increase in the climate-sensitive portion of demand based on the 50
th versus 90$${th}$$ -
null (Ed.)Smart microgrids (SMGs) may face energy rationing due to unavailability of energy resources. Demand response (DR) in SMGs is useful not only in emergencies, since load cuts might be planned with a reduction in consumption but also in normal operation. SMG energy resources include storage systems, dispatchable units, and resources with uncertainty, such as residential demand, renewable generation, electric vehicle traffic, and electricity markets. An aggregator can optimize the scheduling of these resources, however, load demand can completely curtail until being neglected to increase the profits. The DR function (DRF) is developed as a constraint of minimum size to supply the demand and contributes solving of the 0-1 knapsack problem (KP), which involves a combinatorial optimization. The 0-1 KP stores limited energy capacity and is successful in disconnecting loads. Both constraints, the 0-1 KP and DRF, are compared in the ranking index, load reduction percentage, and execution time. Both functions turn out to be very similar according to the performance of these indicators, unlike the ranking index, in which the DRF has better performance. The DRF reduces to 25% the minimum demand to avoid non-optimal situations, such as non-supplying the demand and has potential benefits, such as the elimination of finite combinations and easy implementation.more » « less
